Next Article in Journal
Research on Chinese Speech Emotion Recognition Based on Deep Neural Network and Acoustic Features
Next Article in Special Issue
Defense against Adversarial Swarms with Parameter Uncertainty
Previous Article in Journal
RMHIL: A Rule Matching Algorithm Based on Heterogeneous Integrated Learning in Software Defined Network
Previous Article in Special Issue
A Path-Following Controller for Marine Vehicles Using a Two-Scale Inner-Outer Loop Approach
Article

Robust Nonlinear Tracking Control with Exponential Convergence Using Contraction Metrics and Disturbance Estimation

Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Baochang Zhang
Sensors 2022, 22(13), 4743; https://doi.org/10.3390/s22134743
Received: 9 May 2022 / Revised: 9 June 2022 / Accepted: 20 June 2022 / Published: 23 June 2022
This paper presents a tracking controller for nonlinear systems with matched uncertainties based on contraction metrics and disturbance estimation that provides exponential convergence guarantees. Within the proposed approach, a disturbance estimator is proposed to estimate the pointwise value of the uncertainties, with a pre-computable estimation error bounds (EEB). The estimated disturbance and the EEB are then incorporated in a robust Riemannian energy condition to compute the control law that guarantees exponential convergence of actual state trajectories to desired ones. Simulation results on aircraft and planar quadrotor systems demonstrate the efficacy of the proposed controller, which yields better tracking performance than existing controllers for both systems. View Full-Text
Keywords: robust control; nonlinear control; uncertain systems; disturbance estimation; robot safety robust control; nonlinear control; uncertain systems; disturbance estimation; robot safety
Show Figures

Figure 1

MDPI and ACS Style

Zhao, P.; Guo, Z.; Hovakimyan, N. Robust Nonlinear Tracking Control with Exponential Convergence Using Contraction Metrics and Disturbance Estimation. Sensors 2022, 22, 4743. https://doi.org/10.3390/s22134743

AMA Style

Zhao P, Guo Z, Hovakimyan N. Robust Nonlinear Tracking Control with Exponential Convergence Using Contraction Metrics and Disturbance Estimation. Sensors. 2022; 22(13):4743. https://doi.org/10.3390/s22134743

Chicago/Turabian Style

Zhao, Pan, Ziyao Guo, and Naira Hovakimyan. 2022. "Robust Nonlinear Tracking Control with Exponential Convergence Using Contraction Metrics and Disturbance Estimation" Sensors 22, no. 13: 4743. https://doi.org/10.3390/s22134743

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop